In general, most page visits on the World Wide Web are revisits; in other words, the user is returning to a web page previously visited. As search engines have improved, many users have turned to search engines for navigating to often-visited sites, rather than typing in uniform resource locators (URLs) or using browser bookmarks. A search engine performs the search based on a conventional search method. For example, one known method, described in an article entitled “The Anatomy of a Large-Scale Hypertextual Search Engine,” by Sergey Brin and Lawrence Page, assigns a degree of importance to a document, such as a web page, based on the link structure of the web page. As these navigational queries become increasingly common, users are able to learn which queries will take them to their favorite sites. Bookmarks, however, can provide a benefit to the user. For example, a common use of bookmarks is for navigation to sites that search engines (such as the Google™ Search Engine) do not rank highly or that are otherwise hard to find via a search query.
Accordingly, bookmarks that the user continues to use are a valuable resource for the user. An Internet user often has difficulty propagating bookmarks between the various machines on which the user depends. For example, many users have a computer at work and at home. Often, the bookmarks relied on in the work setting are useful at home as well. In most cases, however, the user must manually synchronize the bookmark lists of the two machines. In addition, conventional methods of organizing bookmarks tend to be limited at best, making it difficult for the user to find a favorite site.
Some users have attempted to solve the propagation problem by using a commercial product that allows the user to store bookmarks on a server on the web, such as BlinkPro (Blink.com, Inc.; www.blinkpro.com) or BookmarkTracker (BookmarkTracker.com, Inc.; www.bookmarktracker.com). Such products allow the bookmarks to be managed and utilized from a browser application. In some cases, the user can also automatically synchronize each of the user's computers to the common list stored on-line. While storing the bookmarks on-line addresses the propagation problem, such systems fail td address the organizational problems inherent in conventional bookmarks.
Various other conventional bookmark-related software products provide the user with functionality to facilitate the use of bookmarks. For example, systems and methods for automatically organizing bookmarks on a client machine, searching previously-stored bookmarks by keyword, and integrating the back, history, and bookmark functions to improve the user's ability to visit previously visited sites have been described (see, e.g., Integrating Back, History and Bookmarks in Web Browsers, Kaasten, S. and Greenberg, S. (2001), In Extended Abstracts of the ACM Conference of Human Factors in Computing Systems (CHI '01), 379-380, ACM Press.). These tools, however, do not effectively leverage the user's preferences to provide personalized search results.
Thus, a need exists to provide an improved system and method for providing personalized network searching.